Your target variable is whatever you want to predict. For this particular dataset, logical choices are probably "death", "event", or "AZT". You'd typically want to use some kind of patient data to predict these outcomes. It wouldn't make much sense, for example, to try to build a model that predicts the treatment course from the death variable - although it's statistically feasible, you'd generally prefer a potentially causative relationship of predicting death from the treatment course. Death cannot possibly be causative of treatment course, since it always occurs after treatment is given.
Even if you could determine the treatment course from whether or not someone died, it's not going to be very useful from a practical, clinical perspective. There are few cases where you'd know whether someone died and didn't know their treatment course (but wanted to know); it'll be far more useful to have someone's current course of treatment, and predict whether they'll die. But in principle, your target can be any variable at all - whether the resulting model is useful, or meaningful, or implementable in practice will depend on what those values actually represent.